Cochlear implants (“CI”s) may restore the ability to hear to deaf or partially deaf individuals by providing electrical stimulation to the auditory nerve via a series of electrodes placed in the cochlea. CIs may successfully provide the ability of almost all post-lingually deaf users (i.e., those who lost their hearing after learning speech and language) to gain an auditory understanding of an environment and/or restore hearing to a level suitable for an individual to understand speech without the aid of lipreading.
One of the key challenges for CI users is to be able to clearly and/or intelligibly understand speech in the context of background noise. Conventional CI devices have been able to aid patients to hear and ascertain speech in a quiet environment, but the performance of such devices quickly degrades in noisy environments. There have been a number of attempts to isolate speech from background noise, e.g., single-channel noise reduction algorithms. Typical single-channel noise reduction algorithms have included applying a gain to the noisy envelopes, pause detection and spectral subtraction, feature extraction and splitting the spectrogram into noise and speech dominated tiles. However, even with these algorithms, speech understanding in the presence of competing talkers (i.e., speech babble noise) remains difficult and additional artifacts are often introduced. Furthermore, mobile communications have created an ever-rising need to be able to clearly and/or intelligibly understand speech while one user may be in a noisy environment. In particular, there is a need for improving speech understanding in telephonic communications, even in the presence of competing talkers (i.e., background speech babble noise).
Despite good progress in improving speech quality and listening ease, little progress has been made in designing algorithms that can improve speech intelligibility. Conventional methods that have been found to perform well in steady background noise generally do not perform well in non-stationary noise (e.g., multi-talker babble). For example, it is often difficult to accurately estimate the background noise spectrum. Moreover, applying noise removal methods to already noisy signals usually introduces distortion and artifacts (e.g., musical noise) to the original signal, which in many cases lead to almost no significant intelligibility improvement. All these reasons make the improvement of speech intelligibility in the presence of competing talkers a difficult problem.
Therefore, there is a need to provide a method or system for noise reduction, particularly for use in or with a cochlear implant, telephone or electronic communications device, that provides speech quality and/or intelligibility.